Position : Machine Learning Engineer
Specialization : NLP and Approximate Reasoning
Level : Junior / Middle
Workload : FTE
sci.AI is a platform for researchers to uncover hypotheses and find new applications of existing biomedical discoveries. Its technology applies natural language processing to read scientific papers and reveals the relationships among points of interest with the help of AI reasoning methods.
We are looking for the machine learning engineer with a specialization in natural language processing. Areas of particular interest include application of neural networks for semantic parsing, clustering of the structured and unstructured textual data and fuzzy reasoning.
You will be part of the R&D team of the sci.AI and collaborate with engineers of Xpansa, pharma companies, and scientists. Daily tasks will include but not limited to implementation of the algorithms to process textual data and reason through the semantic graph, support biologists in conducting knowledge-based research and designing methods of artificial cognition.
Active interest in biomedical progress is a must to share common motivation with the whole team.
- MS/PhD in Computer Science, Math, Physics, Engineering, Statistics or other technical fields;
Experience and Skills
- Familiarity with languages for statistical & scientific computing, such as the Python, R, Scala and associated libraries;
- Experience with core NLP techniques and tasks;
- Ability to select the appropriate analytical techniques based on the characteristics of a problem;
- Knowledge of RDF, OWL, SPARQL, SHACL and experience in ontologies building;
- NoSQL and Graph databases experience;
- Experience using compiled programming languages (e.g., C/C++, Go, Java) for high-performance statistical computing is highly appreciated;
- Experience in development on Unix platforms;
- Experience with the Elasticsearch is highly desired;
- Use version control regularly. We use Gitlab / GitHub;
- Worked on 1 machine learning projects with team of 2 persons at least
- Intermediate English language communication and writing skills at least;
- Interest/ Knowledge in the biomedicine is a must as long as you’ll be involved in analysis of the machine-generated results together with the biologists;
- Deep theoretical knowledge in the fields of computational linguistics, statistics, sets, graph, topology and information theories, machine learning;
- Academic background is highly desired to be familiar with the processes of research conduction and dissemination;
- Strong analytical, synthesizing, critical thinking and reasoning skills;
- Delivering. Problem solver and result oriented;
- Like writing. Project documentation, specification design, communication via email and messengers is an integral part of daily work;
- Punctual, responsible and reliable;
- Quality obsessed;
- Constant learner;
- Interested in biomedical sciences;